Automated speech recognition uses a language model to identify the most likely candidate matching a word or expression used in a natural language context. In many instances, the language model used is built using a generic corpus of text and might not offer the most accurate or optimal representation of natural language for a given topic. For example, in a scientific context, the word “star” may be less likely to follow the phrase “country music” than in an entertainment context. Accordingly, when evaluating an audio signal relating to science, a speech recognition system may achieve more accurate results using a language model specific to the topic of science, rather than a generic language model.